Machine Learning Platform Engineer

Apple Inc

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Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$175,000–$263,300 / yr
Posted
161 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $233k
This role $219k
$160k $311k
below market most similar roles pay here above market

This role pays less than 62% of similar roles. Most pay $211,495–$254,750 — the blue band above. At the midpoint, this role pays about $219k versus about $233k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Machine Learning Platform Engineer

The Machine Learning Platform Engineer, Apple Services Engineering, joins a team building an evaluation platform for generative AI and agent systems. This role involves productionizing ML research by translating prototype code into reliable services and owning features like APIs, SDKs, orchestration components, and evaluation runners. You will build abstractions to help other teams evaluate non-deterministic models while maintaining operational ownership through CI, testing, and metrics. Key technologies include Python, FastAPI, Pydantic, Docker, and containerization. Candidates must demonstrate fluency with the agentic LLM landscape, including tool use, context management, and multi-step reasoning. You will also utilize AI coding tools and potentially work with orchestration frameworks like Temporal.io or Airflow, and distributed compute systems like Ray or Kubernetes to solve complex production ML problems.

What you'll do

  • Build and ship APIs, SDKs, orchestration components, and evaluation runners for the generative AI platform.
  • Translate research prototype code into reliable, production-ready Python services.
  • Develop SDKs and abstractions to improve the developer experience for teams evaluating models and agents.
  • Maintain operational ownership by writing tests, setting up CI, and monitoring production metrics.
  • Identify and resolve codebase issues such as flaky tests, slow builds, and outdated runbooks.
  • Manage the lifecycle of non-deterministic AI evaluations, including prompt iteration and dataset curation.

What we're looking for

  • 4-8 years of software engineering experience building and shipping production services.
  • Strong Python fluency including FastAPI, Pydantic, and the modern Python ecosystem.
  • Fluency with AI coding tools like Claude Code or equivalents in a day-to-day workflow.
  • Familiarity with the agentic LLM landscape including tool use, MCP servers, and agent frameworks.
  • Hands-on experience building evaluations for agents or LLM systems using frameworks like Inspect, Braintrust, or LangSmith.
  • Working knowledge of LLMs in production including prompt iteration, dataset curation, and statistical reasoning.
  • Solid engineering fundamentals in testing, CI/CD, containerization (Docker), and basic observability.
  • Experience with developer platforms, internal tools, or SDKs (preferred).

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